Relationship patterns in major selection of applicants in the tcas system

Name: Phattharamon Phanphaeng

Organization : Chiangmai Rajabhat University. Maehongson College

Email : phattharamon@g.cmru.ac.th

Name: Sancha Panpaeng

Organization : Chiangmai Rajabhat University. Maehongson College

Email : sancha@g.cmru.ac.th

LCSH: Universities and colleges -- Thailand

LCSH: Cluster analysis -- Data processing

LCSH: Information technology -- Study and teaching (Higher)

LCSH: Vocational guidance -- Thailand

LCSH: Educational surveys -- Thailand

Abstract: This research analyzed the selection of the field of study by TCAS applicants. The objectives were 1) to group applicants according to their field of study ranking using the Clustering technique, and 2) to analyze the characteristics of each applicant group. This study used applicant data from the academic years 2019-2025, filtering from a total of 56,970 applicants to focus the analysis specifically on the 10,387 applicants (18.2 percent of the total) who chose fields in the Information Technology and Computer Science group. The research utilized K-Means Clustering, Weighted Preference Encoding, and Mixed-Methods Data Analysis techniques. Data preparation covered several steps, including cleaning the raw data, encoding categorical variables, addressing missing values, scaling features, and finally determining the optimal number of clusters using the Elbow and Silhouette methods. The final analysis revealed four major clusters, each representing distinct patterns among the applicants: Tech-Core, Tech-Data/Al, Tech-Business, and Tech-Creative, with a Silhouette Score of 0.44, indicating a discernible clustering structure, though with some expected overlap characteristic of behavioral data. The research results showed that Applicants in the Information Technology-Computer program have four main interest groups: 1) Technical Technology (Tech-Core): Focuses on computer science, engineering, and program development, with a high male proportion. 2) Data Technology (Tech-Data/Al): Focuses on artificial intelligence and data science, which tend to have the highest GPAX among all groups. 3) Business Technology (Tech-Business): Focuses on business computing and information management, with over 60 percent female applicants. 4) Creative Technology (Tech-Creative): Focuses on multimedia, digital content, and media innovation, combining arts and technology. This group reflects the current trend of Creative Tech and Digital Media careers. Recommendations and Educational Policy Discussion: 1) Educational institutions should design specialized curricula, such as Data/AI, Digital Business, and Creative Tech, to accommodate the diverse interests of students. 2) Guidance agencies should use the results of this group classification as a field recommendation tool (Smart Counseling), matching applicant profiles with appropriate clusters.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2025

Modified: 2026-07-27

Issued: 2026-07-27

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BibliograpyCitation : In IEEE Thailand Section (Computer Chapter) and the Department of Computer Science, Faculty of Science, Chiang Mai University. The 22nd International Joint Conference on Computer Science and Software Engineering (JCSSE 2025) (pp.319-326). Chiang Mai : Chiang Mai University

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